Implemented comprehensive economic calendar system for trading event alerts:
Backend (economic_calendar.py):
- GET /api/economic-calendar/events: Fetch events by days, countries, impact level
- GET /api/economic-calendar/today: Get today's scheduled events
- GET /api/economic-calendar/upcoming: Events within X hours (1-168)
- GET /api/economic-calendar/high-impact: Only critical events (next 30 days)
- GET /api/economic-calendar/by-country/{country}: Country-specific events
- GET /api/economic-calendar/impact-analysis: Gold trading impact analysis
- GET /api/economic-calendar/calendar-view: Calendar view with events by day
- POST /api/economic-calendar/events/{event_id}/notify: Set reminder notifications
- GET /api/economic-calendar/stats: Event statistics and busiest days
Features:
- Sample economic events: NFP, CPI, Unemployment, Fed Rate Decision, ECB Rate
- Impact levels: High/Medium/Low with color coding
- Forecast, previous, and actual values tracking
- Event filtering by country, impact, and days ahead
- Multiple sort options: date, importance, impact
- Notifications 15-120 minutes before events
- Gold trading correlation analysis
- Statistics for 7-day and 30-day windows
Frontend (EconomicCalendar.tsx):
- Calendar overview with event statistics
- Upcoming and high-impact event tabs
- Country-based filtering
- Impact-based color coding (red/yellow/blue)
- Event details: forecast, previous, actual values
- Trading tips for different event types
- Event time display with timezone consideration
- Correlation guidance (USD inverse, rates inverse)
- Visual indicators for pending/actual events
Integration:
- Registered economic_calendar router in main.py
- Added EconomicCalendar tab to App.tsx
- Integrated with navigation system
- Full TypeScript support
Note: Currently uses mock data. In production, integrate with:
- Trading Economics API
- Forexfactory Calendar
- Economic Calendar Pro
- OANDA Calendar
Complete implementation of Phase 1 enhancements including:
Backend:
- UserProfile model for storing user preferences (timezone, trading style, risk tolerance)
- DailyRoutine model for scheduling routines (morning, active_trading, evening)
- RoutineExecution model for tracking routine execution history
- Notification model for managing all types of notifications
- DailyChecklist model for daily task tracking with completion percentage
- HabitTracker model for tracking habits and streaks
Services:
- RoutineService: Handles routine execution with task registry pattern
- RoutineScheduler: Async scheduler for automated routine execution
- NotificationService: Comprehensive notification creation and delivery system
- Support for price alerts, news, routines, reminders, and performance notifications
API Endpoints (daily_helper router):
- User profile: CRUD operations, get/update preferences
- Daily routines: Create, list, execute, track history
- Notifications: CRUD, mark read, batch operations
- Daily checklists: CRUD, item management, completion tracking
- Habits: Create, track, log completions, manage streaks
- Dashboard: Summary endpoint for daily helper overview
Frontend Components:
- UserProfileSetup: Complete user profile configuration with preferences
- NotificationCenter: Bell icon with dropdown, notification management
- HabitTracker: Habit creation, streak tracking, gamification with fire emojis
- DailyChecklistPanel: Checklist management with completion percentage
Schemas:
- Full Pydantic schemas for request/response validation
- Type-safe API contracts
Features:
- Timezone support for international users
- Trading style and risk tolerance preferences
- Automated routine execution with task registry
- Real-time notifications with priority levels
- Habit streaks with motivational badges
- Daily checklist with persistent state
- Completion percentage tracking
- Notes and metadata support
All components are production-ready with error handling and user feedback.
Claude